add mcp

mcp/cli.py

@@ -0,0 +1,3 @@
+# cli.py
+def main():
+    print("Hello MCP!")

mcp/scripts/ask.py

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+import httpx
+import os
+import json
+from context_loader import load_context_from_repo
+from prompt_template import PROMPT_TEMPLATE
+
+OLLAMA_HOST = os.getenv("OLLAMA_HOST", "http://localhost:11434")
+OLLAMA_URL = f"{OLLAMA_HOST}/api/generate"
+OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "syui/ai")
+
+def ask_question(question, repo_path="."):
+    context = load_context_from_repo(repo_path)
+    prompt = PROMPT_TEMPLATE.format(context=context[:10000], question=question)
+
+    payload = {
+        "model": OLLAMA_MODEL,
+        "prompt": prompt,
+        "stream": False
+    }
+
+    #response = httpx.post(OLLAMA_URL, json=payload)
+    response = httpx.post(OLLAMA_URL, json=payload, timeout=60.0)
+    result = response.json()
+    return result.get("response", "返答がありませんでした。")
+
+if __name__ == "__main__":
+    import sys
+    question = " ".join(sys.argv[1:])
+    answer = ask_question(question)
+    print("\n🧠 回答:\n", answer)

mcp/scripts/context_loader.py

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+import os
+
+def load_context_from_repo(repo_path: str, extensions={".rs", ".toml", ".md"}) -> str:
+    context = ""
+    for root, dirs, files in os.walk(repo_path):
+        for file in files:
+            if any(file.endswith(ext) for ext in extensions):
+                with open(os.path.join(root, file), "r", encoding="utf-8", errors="ignore") as f:
+                    content = f.read()
+                    context += f"\n\n# FILE: {os.path.join(root, file)}\n{content}"
+    return context

mcp/scripts/prompt_template.py

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+PROMPT_TEMPLATE = """
+あなたは優秀なAIアシスタントです。
+
+以下のコードベースの情報を参考にして、質問に答えてください。
+
+[コードコンテキスト]
+{context}
+
+[質問]
+{question}
+"""

mcp/setup.py

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+from setuptools import setup
+
+setup(
+    name='mcp',
+    version='0.1.0',
+    py_modules=['cli'],
+    entry_points={
+        'console_scripts': [
+            'mcp = cli:main',
+        ],
+    },
+)